In this paper, we introduce a handy and affordable solution we are developing, for education of human-robot social interaction. The solution consists of a smart device-controlled robot with a 3D printed body, a cloud-based integrated development environment that provides intuitive programming and simulation of the robot, and embedded functions enabling intelligent, natural response of the robot. The outline and architecture of the proposed system are briefly explained.

This demonstration introduces SiCi (Smart ideas for Creative interplay) that brings a single-body robot to life by delivering a variety of contents and then fosters children's creativity and innovation in education.

This paper presents a process to build a classifier in a data-driven way for recognizing engagement of children in a robot-based math quiz game. The process consists of collecting video recordings from HRI experiments; annotating the social signals and engagement states via video analysis; extracting feature vectors from the annotations and training classifiers. We conducted an experiment with 7 participants of 10 -- 11 years of age using an android robot EveR-4. With three coders annotating the video recordings and extracting features by snapshot model with 1-second time window, we achieved 84.83% recall performance.

This paper presents and juxtaposes two different learning processes developed in Israel and in Korea to introduce the concept of systems at early stages of school education, with special focus on the aspects of system structure and behavior. Our findings indicated the students successfully grasped the concept of system through practices of constructing robots and exploring their behaviors.

Presents a situation-driven reconfigurable architecture for a schema-based robot controller which is operating in partially known indoor environments. Instead of the purely repulsive forces from the obstacles, we employ the linear combination of the repulsive and the detouring forces around the obstacle, so that the obstacles generate virtual forces pushing the robot toward the goal rather than just blocking it. By reconfiguring the detouring direction and the activation level of each schema based on the geometric and/or topological information provided by the variable resolution maps, the robot can navigate through the environments in very natural way. Simulation results show that our approach can remarkably improve the intrinsic defects of traditional potential field-bused schemas.